{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "model_evaluation.ipynb",
      "version": "0.3.2",
      "provenance": []
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 2
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython2",
      "version": "2.7.11"
    },
    "kernelspec": {
      "display_name": "Python 2",
      "language": "python",
      "name": "python2"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5ulPig1Bz5hy",
        "colab_type": "text"
      },
      "source": [
        " http://alexadam.ca/ml/2017/05/05/keras-vae.html\n",
        " \n",
        " https://github.com/NicGian/text_VAE\n",
        " \n",
        " https://nicgian.github.io/text-generation-vae/\n",
        " \n",
        " https://s4sarath.github.io/2016/11/23/variational_autoenocder_for_Natural_Language_Processing\n",
        " \n",
        " https://zhusuan.readthedocs.io/en/latest/tutorials/lntm.html#id1\n",
        "\n",
        "http://bjlkeng.github.io/posts/variational-autoencoders/\n",
        "\n",
        "http://bjlkeng.github.io/posts/hyperbolic-geometry-and-poincare-embeddings/\n",
        "\n",
        "http://bjlkeng.github.io/categories/generative-models/\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dc_iaxpMk2d-",
        "colab_type": "code",
        "outputId": "2a2d21ff-c9dd-46cb-88c3-9af705ce03f7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FhWZ1SQglX_j",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import os\n",
        "ADRIEN_PATH = '/content/drive/My Drive/VAE'\n",
        "os.chdir(ADRIEN_PATH)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2E5_XuTGk1U5",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from text_loader_utils import TextLoader\n",
        "import cPickle\n",
        "import numpy as np\n",
        "import tensorflow as tf\n",
        "from variational_model import NVDM\n",
        "from vector_utils import find_norm\n",
        "from tf_common_utils import load_model , save_model\n",
        "\n",
        "np.random.seed(0)\n",
        "tf.set_random_seed(0)\n",
        "\n",
        "def xavier_init(fan_in , fan_out, constant=1): \n",
        "    \"\"\" Xavier initialization of network weights\"\"\"\n",
        "    # https://stackoverflow.com/questions/33640581/how-to-do-xavier-initialization-on-tensorflow\n",
        "#     fan_in = in_and_out[0]\n",
        "#     fan_out = in_and_out[1]\n",
        "    low = -constant*np.sqrt(6.0/(fan_in + fan_out)) \n",
        "    high = constant*np.sqrt(6.0/(fan_in + fan_out))\n",
        "    return tf.random_uniform((fan_in, fan_out), \n",
        "                             minval=low, maxval=high, \n",
        "                             dtype=tf.float32)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hVm9XEH2k1U_",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from sklearn.datasets import fetch_20newsgroups\n",
        "twenty_train = fetch_20newsgroups(subset='train')   \n",
        "data_ = twenty_train.data\n",
        "print(\"Download 20 news group data completed\")\n",
        "A = TextLoader(data_ , min_count = 25)\n",
        "batch_size = 100\n",
        "    # restricting memory usage, TensorFlow is greedy and will use all memory otherwise\n",
        "gpu_opts = tf.GPUOptions(per_process_gpu_memory_fraction=0.9)\n",
        "# initialize the Session"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OizlpCvJk1VC",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "sess = tf.InteractiveSession(config=tf.ConfigProto(gpu_options=gpu_opts))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qCnqzwbFk1VE",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "vae = NVDM(sess , len(A.vocab), 50, [500 , 500] , transfer_fct=tf.nn.tanh , output_activation=tf.nn.softmax, batch_size=100, initializer=xavier_init )"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j6cJk7tQk1VH",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "vae.start_the_model()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nEmAI4Ryk1VK",
        "colab_type": "code",
        "outputId": "216af208-46f4-4ac8-a1a1-07414b3b24ec",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "load_model(vae)"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6-pTaNSmk1VP",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "embedding_matrix = vae.SESS.run(vae.Weights_generator['out_mean'])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_X9_jHzXk1VS",
        "colab_type": "code",
        "outputId": "a07255b9-9562-4813-e036-8cca1d1f47a0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "embedding_matrix.shape"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(50, 8466)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ehhQNRihk1VV",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "embedding_matrix = embedding_matrix.transpose()\n",
        "embedding_matrix = find_norm(embedding_matrix) ####### Normalizing the matrix helps to find cosine similarity so fast"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O3zeCPltk1VX",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from vector_utils import find_similar\n",
        "def word_match(norm_mat , word_ , vocab, vocab_inverse , topN = 10):\n",
        "    \n",
        "    idx = vocab[word_]\n",
        "    similarity_meas , indexes = find_similar(norm_mat , norm_mat[idx])\n",
        "    words = [vocab_inverse[i_x_] for i_x_ in indexes[:topN]]\n",
        "    return zip(words , similarity_meas[:topN])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nlZaFw5Vk1Va",
        "colab_type": "code",
        "outputId": "70de38d0-5e9a-4bf8-caa1-f4c54efe5fb8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 191
        }
      },
      "source": [
        "word_match(embedding_matrix , 'football' , A.vocab , A.vocab_inverse  )"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('football', 1.0000001),\n",
              " ('stadium', 0.85528636),\n",
              " ('basketball', 0.8517698),\n",
              " ('philly', 0.83852017),\n",
              " ('mlb', 0.8359256),\n",
              " ('robbie', 0.83328015),\n",
              " ('anyways', 0.8279561),\n",
              " ('seats', 0.8218862),\n",
              " ('miami', 0.8216685),\n",
              " ('champs', 0.8193858)]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FubyOFLak1Vd",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "################# Pickup the hidden dimensions for all 20 news groups\n",
        "batch_size = 100\n",
        "H_20_grp_nws = []\n",
        "batch_data = A.get_batch(batch_size)\n",
        "batch_id = 0\n",
        "for batch_ in batch_data:\n",
        "\n",
        "            batch_id += 1\n",
        "            collected_data = [chunks for chunks in batch_]\n",
        "            batch_xs , mask_xs , mask_negative  = A._bag_of_words(collected_data)\n",
        "            \n",
        "\n",
        "            feed_dict = {vae.X: batch_xs , vae.dynamic_batch_size:batch_xs.shape[0],\n",
        "                                            vae.MASK:mask_xs}\n",
        "\n",
        "            h_batch    = vae.SESS.run(vae.z, feed_dict= feed_dict)\n",
        "            H_20_grp_nws.extend(h_batch)\n",
        "\n",
        "H_20_grp_nws = np.array(H_20_grp_nws)\n",
        "from sklearn import manifold\n",
        "tsne = manifold.TSNE(n_components=2, init='pca', random_state=0)\n",
        "%time H_tsne = tsne.fit_transform(H_20_grp_nws) ########### Converting to tsne\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cICbQcC5k1Vf",
        "colab_type": "code",
        "outputId": "6742e7e1-37d2-4fc0-f426-706eeef5ad37",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 396
        }
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "%matplotlib inline\n",
        "\n",
        "\n",
        "############ Picking only non - null values after pre-processing ( The non null indexes of data is in self.data_index)\n",
        "newsgroups_target = [twenty_train.target[i] for i in A.data_index]\n",
        "########### Converting targets to One-hot-K Vectors by tf.one_hot for visualization purposes\n",
        "news_target_one_hot = sess.run(tf.one_hot(newsgroups_target , depth=len(set(newsgroups_target))))\n",
        "\n",
        "\n",
        "\n",
        "plt.figure(figsize=(8, 6)) \n",
        "plt.scatter(H_tsne[:, 0], H_tsne[:, 1], c=np.argmax(news_target_one_hot, 1))\n",
        "plt.colorbar()\n"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.colorbar.Colorbar at 0x7f97a00263d0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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7EmM3aj3/Un9N+/untnzCzM/+zu3rnqVSL6I5BC2te9BhEz4rL+fUL27GpzdF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1+vYfIzf+Xt7/0AgGF5g5i16V2qqCQz/QB7y1Nxa53G+qtn+oATWLNnJ15HSHO8/GTEGC45\nbjAAxQ/e7fozBRmZbN7X8CjYz7Zujrp/WZl7L0e8QlWYLJG2aS2YTEWkC/C/QAGhj84jqnpvnWPG\nAy8Ca8KbnlfVX8ZyPUumxpXHcTizewlndi+pt69DWgZf7IpczN3veBBo/BqnrUGdw7kpCAgcm7mV\n0zqtINVzePpKmqeK0wtX0C7zYtfTBIJBznvjCdbv3UlVeO7ivM1ryfWluJbI++24U7l13lzXc63Z\ntZMZs1/mT5Om0CfrWEZ3GMr7ZQvpcsxWPi/tEvdbPiTL6+fRZYurE/GBQIBb583l6ZVLmTlyXMQE\nvXnf3oit02z/4RVueubm8W35vmaL1xwlDg1AajlVwE2qulhEsoBFIjJbVVfUOe7fqhq59mUj2RA3\n02Q3DxobdX9FMMDBYKBe5Z+E0TrfC3iCDsPz1uKV+gnfKwH6Zq50PdW/N63h2/17qxMphFqaB4IB\nbh03juuGjGRQx06c0aM3b184nfNLjqN0x/aIob1cuoqlW75BRLjm2Ev5WcmP8OxvvsUEerXLo0tO\ntmtCXFb2LXPWuQ18OuzWURNct/92/KnV3/9m3KmuxxiTSKq6SVUXh7/fA3wOFLXU9axlappsUH4R\nNx4/hj989u+ox9Wt/JNQdVZWCXqCeCWDgDp4qR1nQD04jvvI39W7t1Hp8r7KqypZvXsbvxg+kRuH\nj661rzAjk9KdkRPq9155jqXTr0NEOC6nL+nBJUD9LuNoBFh99U2ICIFgkG/27CYnNY3slJSI3bgA\ni1y6pg/xOQ5DC91XfllZtpUzjw2N1O2e244/TTyDGXNecz328gGDG/9GzFGltYoviEh3YDAw32X3\nSBH5FPgGuFlVYypLZi1TE5MZx5/Esu/exG1DJ5LrS47C9xG5DIxV4NVNkVuAAwoudd3eO7cDPqf+\nxybd66Mkz71m8S8itO4O2VtRUev1uX0GRD3ezWUDBlev5OJxHLrk5JKdEuqKjTYuODc1jcIIBel/\nNXYiN0RIkPcv/ohA8HDrfEqvfqz+4Y10SKu9NNplAwbz32NOacI7MUeV+Ard54vIwhpfV7ldQkIV\nO/4J3KCqdZdoWgx0U9WBwJ+Af8X6VqxlamKW4fNzUa8T+OXCOQ0f3FhRpqw0t+0VGfz688nMLHmT\ngIYTkSjbuI2SFPfeoFGdutMlM5evdm+vbqGGBhmlcmbXvq4/M75bMdl+P7vrJM1D8uskoPP6DuCB\nxfNZu7v26uf92nfgN2Mn8X9e+HutbtuTirqyaPNGutdogXbNyua9i0O/W048pgsffLPe9dp3jp9M\nTkoq33vpaZZ8u7n6/dw2agLfLTmeW951n3OswOIt3zCssHP1NsdxWHD5f7geb0x9ca/+UtbQ1BgR\n8RFKpE+q6vP1IqiRXFX1NRF5QETyVdV9KakoLJmauNy/9P3mPWErV9h7v6wn537QlSHtQlNhFu3o\nyv0njY94vCPC06dezG8WvcXL61YQVOWUol7cNnQiqeEFs928feF0hjz+oOu+f51Te7CTiDD3wit4\ncPHHPLXyMzwiXNR/EFcOHIqIsOaam1lRtoVNe/cyvkt3zn7+SZaW1V4u7us9uxn21wdYcPl/8MRZ\n59Lv0fvqDQib3L0nncLFI174zsUcDFRxoKqKbH9KdSvX5zgcjDB/tkN6hut2Y5KBhP4T/xn4XFVd\nF2EWkU7AFlVVERlOqLd2WyzXs2Rq4vL3L5ckOoS47Q/4mVd2eEHqD7es4+QuvSIen+1P5Y6RZ3DH\nyDMafY326Rk8NGkKV89+udb2348/naLs7HrHexyHa4eeyLVDT3Q9X7/8Avrlh7qV6ybSQ7buL6ey\nshKfz8eqH/6Yexe8zz8+X0qGz8/vTz6dQQWFtY5P8XhJqbMa0Nm9Snh65bJ6585LTaN7TuR6x8Y0\nSGnpeaajgUuApSLySXjbTKArgKo+BJwLXCMiVcB+4AKNsZKRJVMTl/Kqyth/uIW6dIUAjoQGEsVi\n3ua1zRtQ2Gk9+7DWpbze/oMfsXP3fVRWrSU1ZQi5WTfg9zVPEfmvdu6gb4eOAFw/bDTXDxvdwE/U\n9ttxp7K8bGutuaIZPj8vnHNRs8RnjnItODVGVefRwG8YVb0fuL85rmfJ1MRldGF35m74MrZiAi3U\npev3BGmXso+y/VlUhRNq/Zq9ka3cGXkObXPbW/4qW3fMqK4zu7d8Hfv2v05Rx1fx++Kva1ucG1/r\n0XEcXjnvEr7YXsbb61bTOy+fCd16xB2XMdB6o3lbg43mNXH5xZBTyPY3fjRvhifyc8XmElTh1OIV\njChcTW5KObkp5YwoXIM04c/gk//1UAtGGKIaZNvOmXUKtgdR3cfWbTc3+jyFGe6jcdM8XlJ8zXO/\ne+fl88PBwy2RmuYV32jepGLJ1MSlW1Y7Zk+5ihkDRpPbiKSam9Ly02iCKmT5DjKqaA1XHj+PK4+f\nx4mFa0j3uY+mdbNm744WjDAkGNxOILjTdd/BqoUc3HUHGqw7kr++Dy+9mrw69zXV4+GzK65tljiN\nMQ2zbl4Ttw5pGdw4aCw31qiMdOO8l3hhbe25z+38qbUqB7UEQemWvY10X+1nuYqwvyq56riKk0m0\nh0bf7rmPwv2P4+T9Dcc/JOq5Fl9xLQcqK/ns282U5HckKyWl1v6/Lf2E/5o3l0C4s/u3Y0/lu/2P\nb4Z3YUyMFAgmXwszVtYyNS3iDydNZcm5N3Bp7xPICbdYd1QcYMv+lq3h6nWqGFawlsVburBiWycq\nAh4qAg4fb+pGUB28ItwzeipLzrueUR0iL4vWGjN0HEnFJx0j7q9EEa0isP2KRi24nerzMbyoS71E\nevNbr/GLeXMIhJ9sB4Gfvvcm177xUlzxGxOfOLp4rZvXHE1yU9PITUlr1XVPK4M+nvliGO+s782b\na/vxwCfjmLWmPx9uCo2OrVLllo9e4+U1n/Pk5IsifgDuHRV51ZjmlJ4afXTtQQ0gWo5WxbYIu6ry\n3Kq6db1DXlmdXAu7m6OQJVNjGifaPNR+7ToyqSjyfM5YKUJAPVQGvVQGvazaUUjNtuaBQBW3LXyT\nuz95h68uvoVj0g/P8xTgj6OmMKVH00v6AczasIyJb9zD4Jd+xZQ59/Nx2dqox2dmXRd1f0W4G1j1\nYNTjItl+YH/U/R9tWBfTeY1pFkdQMrVnpqZFVQUjPxOcVtyfqd378/HLX7OrMrZkEY8Hln3IzYPG\n8/45P2qW8z325fvcvfxw+b2v9pZx+by/cv+ICzi50L3UYIq/p+v2Q0QhKB683tiSe6o3+kd84949\nMZ3XGFObtUxNizqta+S5ktO692fqa39JSCKF0PiHQJRkH0lQlQ82r+XvXy5h8dYNqCqqyh9XuK9b\neuuS6M8mhU4R9/nFQyBrJo5Lcf3GyPBFH3Q1qTh6MjemxRwagBTrV5KxlqlpUbcOncjrX6+q99z0\nypJhzNu0plWfp7pxpGlDjbYfKOeC2X/jm327CSqIQEm7An4/+oyII5V3VJRHPWen/IfZVDat3nYv\ngubeT3r66U2Ksa5bR47l9g/fq7d9REER2a0wVckYdwotPLq/NVnL1LSodK+fBd+5juuOO4le2fkM\n69CZpyZdxMwhE1m5c2tC1zwtSs+uLujeWDPnv86a3TvYV1XJ/kAl5VWVLN22iYeXuS2TGOI0MDY4\nLXU4OZn1V1vJzr497kQKMH3QcF445yJSw3V3PcDNw0bx9DkXxn1uY+Jiz0yNaTyfx8OPB47hxwPH\n1NreO7cDTrjQX0tzqD2jM93j442zftCkc1QGA8zdUFqvBVoRDPCP0k/IyHSfNTq+U+8Gz90+91ba\nZc9kb/k/ccRLetrZMXftuhlcUMjKq25otvMZY2qzlqlJmLO6leBtxoQRSbYvhel9h9faVh6o5NYF\nbzTpPEHVqInfLZH2yS7gj8PPb9T5HcdDdub5ZGac06yJ1JikdIQ9M7VPrEmYNK+P+086u1HHFqXn\nRN2fl5Lmut3neJheMpz/t/LjevteWLOc975Z3ajrQ2iJshPyi1w6bRWPp3YqdYD/7D+JF06+Bq8T\n2+o1xhzxjqBu3riTqYjMEJGVIrJcRO6qsf0WESkVkVUiMjne65gj06SuvflOceRpHykeL+OO6cG0\n4n5Rz7P9oPt8Sp/j8H6UJdWaurj5HSeeQbY/FU/1s1YFAV9KVa3jgsDvls/midIPm3R+Y44qlkxD\nRGQCMA0YqKr9gbvD2/sBFwD9gdOAB0TE/jw3ru4ePYWXT/8+5xQPYGJRT4Z06Izf8ZDtS+GS3ifw\n8LjvcGa3ElJiaOEFVCO2WgH2B5q2HuuxOe15d9rVjDmmCx5vAK+/itT0CiTCJ+mu5bMbVQrQmKNP\nHIk0CT9T8Q5Auga4Q8PlWVT12/D2acBT4e1rRKQUGA7Yn+nG1YD2nfj96Mgl/PrlFfCDfiN4dMV8\nDjZyBLDf8XD3yLPomJbJrPXupfPO7dH0Yu85KWncNXIq42b9vsFjAxpkX9VBMn02BcWYI1m83by9\ngTEiMl9E3hWRYeHtRcD6GsdtCG8zJmY3DxrHi2d8n5sGjqVXdn6Dx886azpndS9heEEXRhZ0q7e/\na2Yul/aJvhpLJB1Ssxhf0PAoXYCUVljD1Zg2R4FgMPavJNNgy1RE5oBriZafh38+DzgRGAY8IyJN\nWj1YRK4CrgLo2jXyKh7GAPTJ7UCP7DweW7mg4YNr9AT9fdL3eLb0Ux5d+TGVgQDn9xzIlSUjmjzP\ntKb7RnyX0+fcx8byXRGPcQgNgjLGuEjC7tpYNZhMVXVipH0icg3wvIYeCn0sIkEgH9gIdKlxaOfw\nNrfzPwI8AjB06NAj586aFvPC6mXsjDDgqKYN+3ZTnNO++vV5PQdyXs+BzRaH1/Hw6sQZTJvzAOvK\nt7se848xTZvLasxR5QhKpvF28/4LmAAgIr0BP1AGvARcICIpIlIM9ALqz00wJgb/KP2kUWUeBuQV\ntHgsfsfLK5OuJdWp/3fpyPxijmvfucVjMKZtimOOaRLOM413ANJjwGMisgyoAC4Lt1KXi8gzwAqg\nCviRqiaubpw5ojRmdOzogm60S01vhWjAIw4Lpszk5a8/5aGV75HlT+W2QWdyXDtLpMYcLeJKpqpa\nAVwcYd+vgV/Hc35j3FzS+wQ+/fDVqMf8ZPCEVoomxCMOZ3cbzNndBrfqdY1psxTUCt0bkzjn9DiO\nPjnRR/Om+2wErTFJ7wjq5rVkatocEWHWlCspyengur9TehbHZrd33WeMSSJHUNEGS6amzXr5zCsY\n26m4+j+xFyHbl8JjE86Pa8qLMcY0lS3BZtosj+Pw+MQLWLZtMwu2ric/NYNJnXuR6rUuXmOSnmpS\nFl+IlSVT0+YNaN+JAe3d6ooYY5JaEnbXxsqSqTHGmIRQa5kaY4wx8UjOgUSxsgFIxhhjTJysZWqM\nMab1KUk5XzRWlkyNMcYkxhFUAcmSqTHGmFangB5BLVN7ZmqMMab1qYZaprF+NYKInCYiq0SkVER+\n5rI/RUSeDu+fLyLdY307lkyNMcYccUTEA/wPcDrQD7hQRPrVOWw6sENVewL3AHfGej1LpsYYYxJC\ngxrzVyMMB0pVdXV4hbOngGl1jpkGPB7+/jngFImxFqklU2OMMYnRst28RcD6Gq83hLe5HqOqVcAu\nIKZVMpJqANKiRYvKRGRdouOoIR8oS3QQcWjL8VvsidOW42/LsUPyxd+tpU68hx1vzNHnoq+lGF2q\niCys8foRVX0k3rhilVTJVFXd19RKEBFZqKpDEx1HrNpy/BZ74rTl+Nty7ND2428KVT2thS+xEehS\n43Xn8Da3YzaIiBfIAbbFcjHr5jXGGHMkWgD0EpFiEfEDFwAv1TnmJeCy8PfnAm+pxlbjMKlapsYY\nY0xzUNUqEbkWeAPwAI+p6nIR+SWwUFVfAv4MPCEipcB2Qgk3JpZMo0tY/3szacvxW+yJ05bjb8ux\nQ9uPP6mo6mvAa3W23Vbj+wPAec1xLYmxRWuMMcaYMHtmaowxxsTJkmkEIjJDRFaKyHIRuavG9lvC\npadWicjkRMYYjYjcJCIqIvnh1yIi94Vj/0xETkh0jG5E5Hfh+/6ZiLwgIrk19iX9vW+ofFkyEZEu\nIvK2iKwI/z+/Prw9T0Rmi8iX4X/bJTrWSETEIyJLROSV8OvicFm40nCZOH+iY4xERHJF5Lnw//fP\nRWRkW7r3pjZLpi5EZAKhyhgDVbU/cHd4ez9CD6j7A6cBD4RLViUVEekCnAp8XWPz6UCv8NdVwIMJ\nCK0xZgMDVPV44AvgFmgb976R5cuSSRVwk6r2A04EfhSO92fAXFXtBcwNv05W1wOf13h9J3BPuDzc\nDkLl4pLVvcAsVe0LDCT0PtrSvTc1WDJ1dw1wh6oeBFDVb8PbpwFPqepBVV0DlBIqWZVs7gF+Qmhh\nhkOmAf+rIR8BuSJSmJDoolDVN8OVSAA+IjQ3DNrGvW9M+bKkoaqbVHVx+Ps9hH6ZF1G7xNrjwNmJ\niTA6EekMnAk8Gn4twMmEysJBcseeA4wlNJoUVa1Q1Z20kXtv6rNk6q43MCbcXfSuiAwLb29MeaqE\nEpFpwEZV/bTOrqSP3cUVwOvh79tC/G0hRlfh1TIGA/OBAlXdFN61GShIUFgN+SOhPxoP1ZZrD+ys\n8cdYMt//YmAr8JdwN/WjIpJB27n3po6jdmqMiMwBOrns+jmh+5JHqOtrGPCMiPRoxfCiaiD2mYS6\neJNWtPhV9cXwMT8n1A35ZGvGdjQSkUzgn8ANqrq7Zp1vVVURSboh/yJyFvCtqi4SkfGJjicGXuAE\nYIaqzheRe6nTpZus9964O2qTqapOjLRPRK4Bng9XwvhYRIKEamY2pjxVi4sUu4gcR+gv3k/DvxA7\nA4tFZDhJEjtEv/cAInI5cBZwSo1qJEkTfxRtIcZaRMRHKJE+qarPhzdvEZFCVd0UfhTwbeQzJMxo\nYKqInAGkAtmEnkHmiog33DpN5vu/AdigqvPDr58jlEzbwr03Lqyb192/gAkAItIb8BMqPv0ScIGE\nFpQtJjSY5+OERVmHqi5V1Y6q2l1VuxP6wJ6gqpsJxX5peFTvicCuGt1JSUNETiPUdTdVVctr7Erq\nex/WmPJlSSP8jPHPwOeq+ocau2qWWOwaiwYAAAD4SURBVLsMeLG1Y2uIqt6iqp3D/88vIFQG7iLg\nbUJl4SBJYwcIfybXi0if8KZTgBW0gXtv3B21LdMGPAY8JiLLgArgsnALabmIPEPoP30V8CNVDSQw\nzqZ4DTiD0MCdcuD7iQ0novuBFGB2uHX9kapeHS4DltT3PlL5sgSHFc1o4BJgqYh8Et42E7iD0KON\n6cA64PwExReLnwJPicivgCWEB/gkqRnAk+E/vFYT+kw6tN17f1SzCkjGGGNMnKyb1xhjjImTJVNj\njDEmTpZMjTHGmDhZMjXGGGPiZMnUGGOMiZMlU2OMMSZOlkyNMcaYOFkyNcYYY+L0/wFe//j8ZBtI\nHQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 576x432 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cKBK2p0_EJmV",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd\n",
        "tsne_tfidf_df = pd.DataFrame({'x':H_tsne[:, 0], 'y':H_tsne[:, 1], 'description': newsgroups_text, 'category':newsgroups_target})"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3wXW3bQ3G4H2",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        },
        "outputId": "726908fc-2ccd-4919-f697-a6c8dcfc1a46"
      },
      "source": [
        "tsne_tfidf_df.head()"
      ],
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>category</th>\n",
              "      <th>description</th>\n",
              "      <th>x</th>\n",
              "      <th>y</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>7</td>\n",
              "      <td>From: lerxst@wam.umd.edu (where's my thing)\\nS...</td>\n",
              "      <td>-9.199913</td>\n",
              "      <td>21.605137</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4</td>\n",
              "      <td>From: guykuo@carson.u.washington.edu (Guy Kuo)...</td>\n",
              "      <td>-52.257832</td>\n",
              "      <td>-11.313582</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>4</td>\n",
              "      <td>From: twillis@ec.ecn.purdue.edu (Thomas E Will...</td>\n",
              "      <td>-32.714443</td>\n",
              "      <td>13.952903</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1</td>\n",
              "      <td>From: jgreen@amber (Joe Green)\\nSubject: Re: W...</td>\n",
              "      <td>-20.629852</td>\n",
              "      <td>-44.745380</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>14</td>\n",
              "      <td>From: jcm@head-cfa.harvard.edu (Jonathan McDow...</td>\n",
              "      <td>-31.242035</td>\n",
              "      <td>39.923088</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   category                                        description          x  \\\n",
              "0         7  From: lerxst@wam.umd.edu (where's my thing)\\nS...  -9.199913   \n",
              "1         4  From: guykuo@carson.u.washington.edu (Guy Kuo)... -52.257832   \n",
              "2         4  From: twillis@ec.ecn.purdue.edu (Thomas E Will... -32.714443   \n",
              "3         1  From: jgreen@amber (Joe Green)\\nSubject: Re: W... -20.629852   \n",
              "4        14  From: jcm@head-cfa.harvard.edu (Jonathan McDow... -31.242035   \n",
              "\n",
              "           y  \n",
              "0  21.605137  \n",
              "1 -11.313582  \n",
              "2  13.952903  \n",
              "3 -44.745380  \n",
              "4  39.923088  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hDkiRQMIKeWn",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "4bea8604-71c7-4830-c243-13f7618a59a1"
      },
      "source": [
        "np.argmax(news_target_one_hot, 1)"
      ],
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([7, 4, 4, ..., 3, 1, 8])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1_gbTQENk1Vi",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def find_similiar_docs(index, topN = 10):\n",
        "\n",
        "    a , b = find_similar(find_norm(H_20_grp_nws), find_norm(H_20_grp_nws)[index])\n",
        "    source = data_[index]\n",
        "    similar_results = [data_[i] for i in b[1:topN]]\n",
        "    \n",
        "    return source , zip(similar_results, a[1:topN])"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IG5ZqP5pk1Vl",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "query , res = find_similiar_docs(20)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mlgYdtBKk1Vn",
        "colab_type": "code",
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              "u'From: keith@cco.caltech.edu (Keith Allan Schneider)\\nSubject: Re: <<Pompous ass\\nOrganization: California Institute of Technology, Pasadena\\nLines: 16\\nNNTP-Posting-Host: punisher.caltech.edu\\n\\nlivesey@solntze.wpd.sgi.com (Jon Livesey) writes:\\n\\n[...]\\n>>The \"`little\\' things\" above were in reference to Germany, clearly.  People\\n>>said that there were similar things in Germany, but no one could name any.\\n>That\\'s not true.  I gave you two examples.  One was the rather\\n>pevasive anti-semitism in German Christianity well before Hitler\\n>arrived.  The other was the system of social ranks that were used\\n>in Imperail Germany and Austria to distinguish Jews from the rest \\n>of the population.\\n\\nThese don\\'t seem like \"little things\" to me.  At least, they are orders\\nworse than the motto.  Do you think that the motto is a \"little thing\"\\nthat will lead to worse things?\\n\\nkeith\\n'"
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              "[(u\"From: keith@cco.caltech.edu (Keith Allan Schneider)\\nSubject: Re: Keith Schneider - Stealth Poster?\\nOrganization: California Institute of Technology, Pasadena\\nLines: 19\\nNNTP-Posting-Host: lloyd.caltech.edu\\n\\nmam@mouse.cmhnet.org (Mike McAngus) writes:\\n\\n>Let me see if I understand what you are saying.  In order to talk \\n>knowledgeably about religion, Atheists must first have been so immersed \\n>in a religion that only the rare individual could have left.  \\n\\nNo, you don't understand.  I said that I don't think people can discuss\\nthe subjective merits of religion objectively.  This should be obvious.\\nPeople here have said that everyone would be better off without religion,\\nbut this almost certainly isn't true.\\n\\n>>But really, are you threatened by the motto, or by the people that use it?\\n>The motto is a tool.  Let's try to take away the tool.\\n\\nBut, guns and axes are tools, both of which have been used for murder.\\nShould both be taken away?  That is to say, I don't think motto misuse\\nwarrants its removal.  At least not in this case.\\n\\nkeith\\n\",\n",
              "  0.75049436),\n",
              " (u'From: keith@cco.caltech.edu (Keith Allan Schneider)\\nSubject: Re: Keith Schneider - Stealth Poster?\\nOrganization: California Institute of Technology, Pasadena\\nLines: 25\\nNNTP-Posting-Host: punisher.caltech.edu\\n\\narromdee@jyusenkyou.cs.jhu.edu (Ken Arromdee) writes:\\n\\n>>But, if you were to discuss the merits of racism, or its psycholgical\\n>>benefits, you would do well to have experienced it personally.\\n>When you speak of \"experiencing religion\" you mean someone should believe in\\n>a religion.\\n\\nThat\\'s right, and this is pretty impossible, right?  It would be ideal if\\nwe could believe for a while, just to try out religion, and only then\\ndetermine which course of thought suits us best.  But again, this is not\\npossible.  Not that religion warrants belief, but the belief carries with\\nit some psychological benefits.  There are also some psychological\\nburdens, too.\\n\\n>When you speak of \"experiencing racism\", do you mean that someone should\\n>believe in racism, or that they should have racist things done to them?  For\\n>parallelism, the former must be what you meant, but it seems to be an odd\\n>usage of the phrase.\\n\\nWell, if there were some psychological or other benefits gained from racism,\\nthey could only be fully understood or judged by persons actually \"believing\"\\nin racism.  Of course, the parallel happens to be a poor one, but you\\noriginated it.\\n\\nkeith\\n',\n",
              "  0.71483386),\n",
              " (u'From: livesey@solntze.wpd.sgi.com (Jon Livesey)\\nSubject: Re: <<Pompous ass\\nOrganization: sgi\\nLines: 20\\nDistribution: world\\nNNTP-Posting-Host: solntze.wpd.sgi.com\\n\\nIn article <1qlef4INN8dn@gap.caltech.edu>, keith@cco.caltech.edu (Keith Allan Schneider) writes:\\n|> livesey@solntze.wpd.sgi.com (Jon Livesey) writes:\\n|> \\n|> [...]\\n|> >>The \"`little\\' things\" above were in reference to Germany, clearly.  People\\n|> >>said that there were similar things in Germany, but no one could name any.\\n|> >That\\'s not true.  I gave you two examples.  One was the rather\\n|> >pevasive anti-semitism in German Christianity well before Hitler\\n|> >arrived.  The other was the system of social ranks that were used\\n|> >in Imperail Germany and Austria to distinguish Jews from the rest \\n|> >of the population.\\n|> \\n|> These don\\'t seem like \"little things\" to me.  At least, they are orders\\n|> worse than the motto.  Do you think that the motto is a \"little thing\"\\n|> that will lead to worse things?\\n\\nYou don\\'t think these are little things because with twenty-twenty\\nhindsight, you know what they led to.\\n\\njon.\\n',\n",
              "  0.6982823),\n",
              " (u'From: keith@cco.caltech.edu (Keith Allan Schneider)\\nSubject: Re: <<Pompous ass\\nOrganization: California Institute of Technology, Pasadena\\nLines: 57\\nNNTP-Posting-Host: punisher.caltech.edu\\n\\nAndrew Newell <TAN102@psuvm.psu.edu> writes:\\n\\n>>I think you should support your first claim, that people will simply\\n>>harass me no matter what, as I doubt this is true. I think *some* of the\\n>>theists will be at a loss, and that is enough reason for me.\\n>Because \"IN GOD WE TRUST\" is a motto on the coins, and the coins\\n>are a representation of the government, christians are given\\n>ammunition here to slander atheists as unpatriotic.\\n\\nSo, we should ban the ammunition?  Why not get rid of the guns?\\n\\n>And yes, I have heard this used in conversation with christians.\\n>Sure, they may fall back on other things, but this is one they\\n>should not have available to use.\\n\\nIt is worse than others?  The National Anthem?  Should it be changed too?\\nGod Bless America?  The list goes on...\\n\\n>Imagine if the next year\\'s set of coins were labeled with\\n>the motto:   \"GOD IS DEAD\".\\n>Certainly, such a statement on U.S. coins would offend almost\\n>every christian.  And I\\'d be tempted to rub that motto in the\\n>face of christians when debunking their standard motto slinging\\n>gets boring.\\n\\nThen you\\'d be no better than the people you despise.\\n\\n>Any statement printed on an item that represents\\n>the government is an endorsement by the government.\\n\\nOh?\\n\\n>The coin motto is an endorsement of trusting in god.\\n\\nAn endorsement, or an acknowledgement?  I think gods are things that people\\nare proud of, but I don\\'t think the motto encourages belief.\\n\\n>I don\\'t particularly feel like trusting in god,\\n>so the government IS putting me down with every\\n>coin it prints.\\n\\nIs it?\\n\\n[...]\\n>For the motto to be legitimate, it would have to read:\\n>   \"In god, gods, or godlessness we trust\"\\n\\nWould you approve of such a motto?\\n\\n>Whether the motto was intended to be anti-atheist or not,\\n>it turns up as an open invitation to use as an anti-atheist tool.\\n\\nAnd removing the tool will solve the problem?\\n\\nOr will it increase the problem?\\n\\nkeith\\n',\n",
              "  0.6874158),\n",
              " (u\"From: keith@cco.caltech.edu (Keith Allan Schneider)\\nSubject: Re: <Political Atheists?\\nOrganization: California Institute of Technology, Pasadena\\nLines: 20\\nNNTP-Posting-Host: punisher.caltech.edu\\n\\nlivesey@solntze.wpd.sgi.com (Jon Livesey) writes:\\n\\n>Perhaps the chimps that failed to evolve cooperative behaviour\\n>died out, and we are left with the ones that did evolve such\\n>behaviour, entirely by chance.\\n\\nThat's the entire point!\\n\\n>Are you going to proclaim a natural morality every time an\\n>organism evolves cooperative behaviour?\\n\\nYes!\\n\\nNatural morality is a morality that developed naturally.\\n\\n>What about the natural morality of bee dance?\\n\\nHuh?\\n\\nkeith\\n\",\n",
              "  0.6555981),\n",
              " (u'From: keith@cco.caltech.edu (Keith Allan Schneider)\\nSubject: Re: Political Atheists?\\nOrganization: California Institute of Technology, Pasadena\\nLines: 57\\nNNTP-Posting-Host: lloyd.caltech.edu\\n\\nmmwang@adobe.com (Michael Wang) writes:\\n\\n>I was looking for a rigorous definition because otherwise we would be\\n>spending the rest of our lives arguing what a \"Christian\" really\\n>believes.\\n\\nI don\\'t think we need to argue about this.\\n\\n>KS>Do you think that the motto points out that this country is proud\\n>KS>of its freedom of religion, and that this is something that\\n>KS>distinguishes us from many other countries?\\n>MW>No.\\n>KS>Well, your opinion is not shared by most people, I gather.\\n>Perhaps not, but that is because those seeking to make government\\n>recognize Christianity as the dominant religion in this country do not\\n>think they are infringing on the rights of others who do not share\\n>their beliefs.\\n\\nYes, but also many people who are not trying to make government recognize\\nChristianity as the dominant religion in this country do no think\\nthe motto infringes upon the rights of others who do not share their\\nbeliefs.\\n\\nAnd actually, I think that the government already does recognize that\\nChristianity is the dominant religion in this country.  I mean, it is.\\nDon\\'t you realize/recognize this?\\n\\nThis isn\\'t to say that we are supposed to believe the teachings of\\nChristianity, just that most people do.\\n\\n>Like I\\'ve said before I personally don\\'t think the motto is a major\\n>concern.\\n\\nIf you agree with me, then what are we discussing?\\n\\n>KS>Since most people don\\'t seem to associate Christmas with Jesus much\\n>KS>anymore, I don\\'t see what the problem is.\\n>Can you prove your assertion that most people in the U.S. don\\'t\\n>associate Christmas with Jesus anymore?\\n\\nNo, but I hear quite a bit about Christmas, and little if anything about\\nJesus.  Wouldn\\'t this figure be more prominent if the holiday were really\\nassociated to a high degree with him?  Or are you saying that the\\nassociation with Jesus is on a personal level, and that everyone thinks\\nabout it but just never talks about it?\\n\\nThat is, can *you* prove that most people *do* associate Christmas\\nmost importantly with Jesus?\\n\\n>Anyways, the point again is that there are people who do associate\\n>Christmas with Jesus. It doesn\\'t matter if these people are a majority\\n>or not.\\n\\nI think the numbers *do* matter.  It takes a majority, or at least a\\nmajority of those in power, to discriminate.  Doesn\\'t it?\\n\\nkeith\\n',\n",
              "  0.65489703),\n",
              " (u' zaphod.mps.ohio-state.edu!wupost!uunet!olivea!sgigate!odin!fido!solntze.wpd.sgi.com!livesey\\nSubject: Re: <Political Atheists?\\nFrom: livesey@solntze.wpd.sgi.com (Jon Livesey)\\nOrganization: sgi\\nNNTP-Posting-Host: solntze.wpd.sgi.com\\nLines: 28\\n\\nIn article <1pi8h5INNq40@gap.caltech.edu>, keith@cco.caltech.edu (Keith Allan Schneider) writes:\\n|> (reference line trimmed)\\n|> \\n|> livesey@solntze.wpd.sgi.com (Jon Livesey) writes:\\n|> \\n|> [...]\\n|> \\n|> >There is a good deal more confusion here.   You started off with the \\n|> >assertion that there was some \"objective\" morality, and as you admit\\n|> >here, you finished up with a recursive definition.   Murder is \\n|> >\"objectively\" immoral, but eactly what is murder and what is not itself\\n|> >requires an appeal to morality.\\n|> \\n|> Yes.\\n|> \\n|> >Now you have switch targets a little, but only a little.   Now you are\\n|> >asking what is the \"goal\"?   What do you mean by \"goal?\".   Are you\\n|> >suggesting that there is some \"objective\" \"goal\" out there somewhere,\\n|> >and we form our morals to achieve it?\\n|> \\n|> Well, for example, the goal of \"natural\" morality is the survival and\\n|> propogation of the species. \\n\\n\\nI got just this far.   What do you mean by \"goal\"?    I hope you\\ndon\\'t mean to imply that evolution has a conscious \"goal\".\\n\\njon.\\n',\n",
              "  0.6426237),\n",
              " (u'From: keith@cco.caltech.edu (Keith Allan Schneider)\\nSubject: Re: Keith Schneider - Stealth Poster?\\nOrganization: California Institute of Technology, Pasadena\\nLines: 26\\nNNTP-Posting-Host: lloyd.caltech.edu\\n\\ncmtan@iss.nus.sg (Tan Chade Meng - dan) writes:\\n\\n>I somewhat agree with u.  However, what it comes to (theist) religion, \\n>it\\'s a different matter.  That\\'s because religion is like a drug, once u\\n>use it, it\\'s very difficult to get out of it.  That\\'s because in\\n>order to experience a religion, u necessarily have to have blind faith,\\n>and once u have the blind faith, it\\'s very diffcult for you to reason\\n>yourself back to atheism again.\\n>Therefore, it\\'s unreasonable to ask people to try religion in order to\\n>judge it.  It\\'s like asking people to \"try dying to find out what\\n>death is like\".\\n\\nWell now, we can\\'t judge death until we are dead right?  So, why should\\nwe judge religion without having experienced it?  People have said that\\nreligion is bad by any account, and that it is in no way useful, etc.,\\nbut I don\\'t totally agree with this.  Of course, we cannot really say\\nhow the religious folk would act had they not been exposed to religion,\\nbut some people at least seemed to be helped in some ways by it.\\n\\nSo basically, we can not judge whether religion is the right route for\\na given individual, or even for a general population.  We can say that\\nit is not best for us personally (at least, you can choose not to use\\nreligion--might be hard to try to find out its benefits, as you state\\nabove).\\n\\nkeith\\n',\n",
              "  0.638653),\n",
              " (u\"From: keith@cco.caltech.edu (Keith Allan Schneider)\\nSubject: Re: some thoughts.\\nOrganization: California Institute of Technology, Pasadena\\nLines: 37\\nNNTP-Posting-Host: punisher.caltech.edu\\nKeywords: Dan Bissell\\n\\nbissda@saturn.wwc.edu (DAN LAWRENCE BISSELL) writes:\\n\\n>First I want to start right out and say that I'm a Christian.\\n\\nWell, this is alt.atheism.  I hope you arent here to try to convert anyone.\\n\\n>It makes sense to be one.\\n\\nMany would disagree.\\n\\n[...]\\n>The book says that Jesus was either a liar, or he was crazy ( a \\n>modern day Koresh) or he was actually who he said he was.\\n\\nWell, you shouldn't give any particular book too much weight.  Actually,\\nI don't think that any of these statements is correct.  It is more likely\\nthat most of Jesus' fame was attributed to him after his death by those\\nwho had some strong motives...\\n\\n[...]\\n>Some other things to note.  He fulfilled loads of prophecies in \\n>the psalms, Isaiah and elsewhere in 24 hrs alone.\\n\\nWhat's a prophecy, and what's so significant about them?\\n\\n>I don't think most people understand what a Christian is.\\n\\nI think we understand.\\n\\n>It is certainly not what I see a lot in churches.  Rather I think it \\n>should be a way of life, and a total sacrafice of everything for God's \\n>sake.\\n\\nWell, sell your computer and donate you life to your religion now...\\nDon't waste any time.\\n\\nkeith\\n\",\n",
              "  0.6221582)]"
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